Task 2: Similarity Measurement This task is about the difference between using euclidean distance or cosine similarity as the similarity measurement between two document vectors in a vector space model. The euclidean distance of two vectors x-(x1, , Xn) and ?-(y1, , yn) ?s defined as The cosine similarity between the same vectors is defined as ?-? cos(x, y) - 1 Xi 1Vi Explain why it almost always is a bad choice to use euclidean distance for estimating the similarity between two documents vectors in a vector space model over tf-idf weights. Explain why cosine similarity is a better choice and how it alleviates the problem of using the euclidean distance